Influenza causes a major public health burden, as evidenced by the tremendous efforts required to prevent and treat disease during the recent H1N1 pandemic. The primary influenza prevention method is vaccination;however, the effectiveness of influenza vaccine varies depending upon host factors and vaccine characteristics that include individual immune response and the match between the vaccine strains and circulating strains in any given year. Therefore, vaccine effectiveness (VE) varies annually, particularly among elderly persons, and is a subject of international controversy. We propose an age-matched case-control study of the effectiveness of influenza vaccine in the UPMC- Health System. Using case-control methods, we propose to calculate the effectiveness of influenza vaccines against laboratory-confirmed influenza virus infections among outpatients in three age groups: 6 months-18 yrs, 19-49 yrs, and 50+yrs. We will use existing syndromic surveillance to identify when influenza-like illness (ILI) begins in the community;recruit, consent and enroll outpatients with for medically-attended acute respiratory illness (MAARI);test with reverse transcriptase-polymerase chain reaction (RT-PCR) to identify cases and controls;determine vaccination status using primarily the UPMC electronic health record (EHR) and the electronic statewide vaccine registry (PA-SIIS);quantify potential confounders and effect modifiers using the EHR (e.g., Charleson co-morbidity score) and survey methodology;determine VE;and conduct sensitivity analyses about the impact of potential unmeasured confounders. Additionally we will determine the local epidemiology, burden and course of influenza illness and estimate the population-based attack rate for laboratory-confirmed influenza, using agent-based modeling at the Pittsburgh Supercomputing Center. The proposed study is based on a strong foundation of our ongoing syndromic surveillance of influenza, advanced biomedical informatics using system-wide electronic medical record, broadly-based research to increase vaccination rates, clinical context of multiplex respiratory virus testing, and agent-based modeling to produce population estimates of disease burden and cost and involves a well-published team of investigators. Optional Objective A Overall Priority Score: 20 Optional Objective C Overall Priority Score: 1